customerio-deploy-pipeline
Deploy Customer.io integrations to production cloud platforms. Use when deploying to Cloud Run, Vercel, AWS Lambda, or Kubernetes with proper secrets management and health checks. Trigger: "deploy customer.io", "customer.io cloud run", "customer.io kubernetes", "customer.io lambda", "customer.io vercel".
84
82%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-crafted skill description that clearly defines its scope (Customer.io deployment to specific cloud platforms), includes explicit 'Use when' guidance with platform names, and provides natural trigger terms. The description is concise yet comprehensive, covering capabilities (secrets management, health checks) and specific platforms, making it easy for Claude to distinguish from other deployment or Customer.io skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and platforms: deploying to Cloud Run, Vercel, AWS Lambda, Kubernetes, with proper secrets management and health checks. These are concrete, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (deploy Customer.io integrations to production cloud platforms with secrets management and health checks) and 'when' (explicit 'Use when' clause specifying platforms, plus explicit trigger terms). | 3 / 3 |
Trigger Term Quality | Includes explicit trigger terms that users would naturally say: 'deploy customer.io', 'customer.io cloud run', 'customer.io kubernetes', 'customer.io lambda', 'customer.io vercel'. These cover the natural variations of how users would phrase deployment requests for this specific integration. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific combination of Customer.io + deployment platforms. The trigger terms are narrowly scoped to Customer.io deployments, making it very unlikely to conflict with generic deployment skills or generic Customer.io skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides highly actionable, production-ready code examples for deploying Customer.io integrations across multiple cloud platforms, which is its strongest quality. However, it suffers from being overly long by inlining all platform-specific configurations rather than splitting them into separate files, and the workflow lacks clarity on whether steps are sequential or pick-one alternatives. The blue-green deployment section is well-structured with validation, but other deployment paths lack similar verification steps.
Suggestions
Split per-platform deployment configs into separate files (e.g., CLOUD-RUN.md, VERCEL.md, K8S.md, LAMBDA.md) and keep SKILL.md as a concise overview with links to each.
Clarify at the top that Steps 1/3/4 are alternative deployment targets (pick one), not a sequential workflow, and restructure accordingly.
Add explicit post-deploy validation steps for each platform (not just blue-green), such as verifying the health endpoint returns 200 after deployment.
Document the rollback procedure that is mentioned in the checklist but never actually provided.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is quite long (~250 lines) covering four deployment targets plus blue-green deployment. While the code examples are useful, covering all platforms in one file is verbose—Claude doesn't need full boilerplate K8s manifests or complete GitHub Actions workflows spelled out. Some of this could be split into separate files per platform. | 2 / 3 |
Actionability | Every section provides fully executable, copy-paste-ready code: complete GitHub Actions workflow YAML, TypeScript health check endpoint, Vercel serverless function, Kubernetes manifests, and a blue-green deployment bash script. All are concrete and specific with real commands and configurations. | 3 / 3 |
Workflow Clarity | Steps are numbered and sequenced, and the blue-green deployment includes a health check validation gate before traffic shifting. However, there's no overall deployment workflow tying the steps together—it's unclear if all steps are needed or just pick-one-per-platform. The checklist is helpful but there's no explicit rollback procedure despite listing it as a checklist item, and no validation feedback loop for the initial deployment steps (1, 3, 4). | 2 / 3 |
Progressive Disclosure | The skill references external resources and a next-steps skill, but the content itself is monolithic—all four platform deployments are inline rather than split into separate files. A better structure would have a brief overview with links to per-platform deployment guides (e.g., CLOUD-RUN.md, VERCEL.md, K8S.md). | 2 / 3 |
Total | 9 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
70e9fa4
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.